Flexible Automation and Intelligent Manufacturing: The Future of Automation and Manufacturing: Intelligence, Agility, and Sustainability: Proceedings of FAIM 2025, June 21–24, 2025, New York City, NY, USA, Volume 2
Author:   Krishnaswami Srihari ,  Mohammad T. Khasawneh ,  Sangwon Yoon ,  Daehan Won
Publisher:   Springer Nature Switzerland AG
ISBN:  

9783032056092


Pages:   699
Publication Date:   16 October 2025
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Flexible Automation and Intelligent Manufacturing: The Future of Automation and Manufacturing: Intelligence, Agility, and Sustainability: Proceedings of FAIM 2025, June 21–24, 2025, New York City, NY, USA, Volume 2


Overview

This book reports on cutting-edge research and developments in manufacturing, giving a special emphasis to intelligent, agile and sustainable solutions. It covers applications of machine learning in manufacturing and advances in cyber-physical systems, human-robot collaboration, and machine tools and assembly systems. It also reports on advances in logistics and supply chain, and lean manufacturing. Based on the proceedings of the 33rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2025), held on 21–24, 2025, in New York City, NY, USA, this second volume of a 2-volume set provides academics and professionals with extensive, technical information on trends and technologies in manufacturing, yet it also discusses challenges and practice-oriented experience in all the above-mentioned areas.

Full Product Details

Author:   Krishnaswami Srihari ,  Mohammad T. Khasawneh ,  Sangwon Yoon ,  Daehan Won
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032056092


ISBN 10:   3032056098
Pages:   699
Publication Date:   16 October 2025
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

.- Application of Ensemble Learning to Classify Failures in Lithium-ion Batteries.- Implementation of a Reinforcement Learning Application for Production Scheduling Including Practical Constraints.- Prediction of Machined Surface Roughness Using Cutting Load and Machining History Data.- Prediction of Tensile Strength and Impact Strength in Fused Deposition Modeling Using a Machine Learning Pipeline, etc.

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